The United Nations notes that water use has been growing at more than twice the rate of population increase in the last century, and an increasing number of regions are chronically short of water. By 2025 two-thirds of the world's population could be under water stress conditions as a result of increased populations. Water, especially potable water, is essential for all socio-economic developments and for maintaining a healthy population. As populations increase across the globe they call for an increased allocation of clean water for use, resulting in increased water scarcity.
One method to address water scarcity and conserve resources is the detection of leaks and other events occurring in water utility networks. Some experts estimate that losses due to leaks and theft amount to 25-30% of the water flowing through water utility networks. Therefore, a significant amount of water may be conserved merely by addressing the water loss in systems already controlled by humans.
Old and poorly constructed pipelines, inadequate corrosion protection, poorly maintained valves, and mechanical damage are some of the factors that contribute to water loss. Additionally, water leaks reduce the supply pressure in the system, and as a result the utility must raise pressure in the system to make up for the losses. Raising the system pressure results in more water being pumped and raises the energy consumption of the water utility. Indeed, water distribution networks are the single biggest consumers of energy in many countries. By identifying and correcting water leaks and other network issues, utilities can conserve water for future use and dramatically reduce energy consumption.
Adding to the difficulty is that most water utility networks are large and complex, and have been built through piecemeal growth, with many pipes in arbitrary configurations to serve specific geographical needs that develop over time. Further, most water utility networks lack accurate, frequent, real-time customer consumption metering, which might allow for a simple conservation of mass input and output accounting. Additionally, water utility networks are designed to deliver water to a large number of consumers, whose individual behavior is unpredictable and subject to change due to many factors. Such factors include, for example, weather changes and natural events (e.g., hot weather increases consumption, as do droughts), holidays and atypical social events (e.g., causing consumers to remain home and water use to increase in residential networks and decrease in business neighborhoods), and demographic changes in neighborhoods over time.
Existing methods for leak detection in water utility networks do not adequately address these problems. For example, commercially available hardware leak detection devices used for field surveys, such as acoustic sensors, can be effective at pinpointing a leak within a given area, but are expensive to install and operate and do not provide rapid discovery and blanket coverage of a whole network. Existing water IT systems, such as the Advise™ Water Leakage Management available from ABB, attempt to make some use of meter data but that use is simplistic and thus the results are of limited usefulness. For example, the systems do not accurately identify or report in real time on specific individual events such as leaks or other network events, do not identify meter faults or adverse water quality conditions, lack statistical analysis needed to accurately understand routine network operation, and suffer other deficiencies. Furthermore, the systems currently in use lack the ability to detect energy loss or water thefts. A key failing of most current approaches is a lack of deep statistical modeling of the many unmetered components of water networks, most notably the water consumption by service customers, which is frequently modeled by very rudimentary techniques, yet has a profound impact on any analysis of the network.
Supervisory Control and Data Acquisition (“SCADA”) systems have become increasingly available in water utilities throughout the world, collecting data from a variety of meters within the network, measuring quantities such as flow and pressure. However, at most utilities these systems are used by a few skilled operators mainly for ongoing operational needs; utilities make little use of the historical data accumulated in their systems to automatically (or otherwise) detect leaks and other anomalous network events. Furthermore, any anomaly detection is usually limited to single-sensor fixed-bound alerts, leading either to low sensitivity or to a high proportion of false alerts.
Water utility network operators continue to add even more meters to monitor the activity of distribution systems. While this does provide greater amounts of data regarding the network, and hence greater potential for understanding events within the network, the increased volume of data often serves merely to confuse network operators further, and exacerbate the already difficult “needle in a haystack” aspect of water network monitoring. Moreover, the placement of more meters is not usually optimized to improve the usefulness of data being received from the overall system for advanced monitoring purposes. As a result, the increased volumes of data describing network activity are unorganized and often confusing and do not allow network operators to make any better decisions about the status of the water utility network.
As such, there exists a need for improved systems and methods to better analyze data retrieved from a water utility network and data about the utility network and the consumption of its resources to facilitate improved management of these resources.